#EEGManyPipelines

Project description

The EEGManyPipelines project was designed to address the challenges posed by variable data analysis practices to the replicability of findings in psychology and cognitive neuroscience. To this end, we sent a single EEG dataset together with a set of eight hypotheses to a large number of laboratories worldwide. Participants were instructed to analyze the data using their standard laboratory pipelines and to provide a comprehensive report of their procedures. Data collected included prior and posterior belief questionnaires concerning each hypothesis, the outcomes of the hypothesis tests, the pre-processed EEG data, the scripts used for analysis, and detailed documentation of all processing steps. The main goal of the project is to map the real-life analytical flexibility in EEG research and its effects on the reported results.

 

Funding bodies

The project has been funded by the DFG priority program “META-REP: A Meta-scientific Programme to Analyse and Optimise Replicability in the Behavioural, Social, and Cognitive Sciences”  (DFG; BU 2400/11-1) and Riksbankens Jubileumsfond (grant number: P21-0384).

 

Publications

Trübutschek D, Yang YF, Gianelli C, Cesnaite E, Fischer NL, Vinding MC, Marshall TR, Algermissen J, Pascarella A, Puoliväli T, Vitale A, Busch NA, Nilsonne G. EEGManyPipelines: A Large-scale, Grassroots Multi-analyst Study of Electroencephalography Analysis Practices in the Wild. J Cogn Neurosci. 2024 Feb 1;36(2):217-224. doi: 10.1162/jocn_a_02087. PMID: 38010291.

Visual long-term memory

Why is it that some events are remembered for a long time, while others are forgotten so quickly? How does this relate to computer vision? Could we predict if an image will be remembered or forgotten by studying event-related potentials (ERP)? To answer these questions we combine a number of different techniques including EEG and deep neural networks into two separate projects.

• Comparing scene representation in human memory and neural networks

  Project description

  The DeepMem project addresses the question why people remember certain images but others not and how features of complex visual scenes influence the process of perception and memory. To study this we collect behavioral data online and in the lab as well as EEG data.

  This project builds a bridge between experimental psychology and computer vision. We quantify image features with neural networks to compare scene representations in human memory and neural networks and to further analyze and predict how memorable an image is. But also to answer the question what the "data format" of visual memory is.

   

  Funding bodies

  This project is funded by the German Research Foundation (BU2400/14-1).

   

  Publications

  Broers, N., Busch, N. The effect of intrinsic image memorability on recollection and familiarity. Mem Cogn 49, 998–1018 (2021). https://doi.org/10.3758/s13421-020-01105-6

• Memory effects in the continuous recognition task

  The typical paradigm to study recognition memory includes an initial encoding stage and a subsequent test phase. Using such a paradigm, numerous studies have identified several memory-related ERP components: subsequent-memory effect (SME) during the encoding phase, and late old/new effects during the recognition phase. These effects have rarely been studied in the continuous recognition task (CRT) in which items are presented in a continuous sequence and the participants’ task is to report whether it is novel or repeated.
  Within the current study, we aim to investigate (i) whether conventional ERP memory effects are found in a CRT paradigm, (ii) the SME over repeated presentations of an item and as a function of temporal lag between initial and subsequent presentation, and (iii) to investigate if the old/new effects reflect memory strength.

Olfactory Perception

Our sense of smell shapes our emotions, memories, and even our behavior—yet we often take it for granted until it changes or fades. What we smell is not just determined by the molecules in the air but also by our expectations: prior experiences and contextual cues influence how we perceive odors and how smells, in turn, shape our perception of other stimuli.

In our research, we investigate how expectations modulate olfactory perception, as well as how adaptation and habituation alter our sensitivity to odors over time—such as why your favorite perfume no longer smells as it once did. Using psychophysical experiments and EEG, we aim to understand the neural mechanisms underlying these processes.

Neural Oscillations and Perception

Our perception of the world isn't static; it fluctuates, leading us to sometimes notice subtle details and at other times miss obvious ones. These variations can be linked to spontaneous brain activity, particularly alpha-band oscillations—rhythmic patterns in the brain that occur even in the absence of external stimuli.

Our research explores how these spontaneous neural oscillations influence what we perceive. For instance, we've found that the strength of alpha oscillations before a visual stimulus appears can bias our perception of contrast, making an image seem more or less vivid. Additionally, these oscillations can affect our baseline neural excitability, altering our likelihood of detecting faint stimuli. By combining behavioral experiments with EEG recordings, we aim to uncover the mechanisms by which these intrinsic brain rhythms shape our perceptual experiences.

 

- Balestrieri, E., & Busch, N. A. (2022). Spontaneous alpha-band oscillations bias subjective contrast perception. Journal of Neuroscience, 42(25), 5058-5069.

- Iemi, L., Chaumon, M., Crouzet, S. M., & Busch, N. A. (2017). Spontaneous neural oscillations bias perception by modulating baseline excitability. Journal of Neuroscience, 37(4), 807-819.

- Samaha, J., Iemi, L., Haegens, S., & Busch, N. A. (2020). Spontaneous brain oscillations and perceptual decision-making. Trends in cognitive sciences, 24(8), 639-653.

 

• Iconic Memory

  Project Description

  In this project, we investigate the relationship between spontaneous alpha fluctuations and visual short-term memory (iconic memory). Our iconic memory essentially takes a “screenshot” of our visual field. This “screenshot” is represented for a couple hundred milliseconds during which we have access to a multitude of information. We look into the way that ongoing brain states influence this information and the performance of our iconic memory. One particular aspect we focus on is the spontaneous lateralization of alpha over the hemispheres as well as its relationship with attention. To evaluate this we collect EEG data, as well as eye-tracking, breathing, ECG, and behavioral data.

   

  Publications

  Smith, P. J. C., & Busch, N. A. (2024). Spontaneous alpha-band lateralization extends persistence of visual information in iconic memory by modulating cortical excitability. bioRxiv, 2024-10.